Job Summary
Task Description: Job Description
Design, develop, deploy & support enterprise-grade Agentic AI solutions on Google Gemini Enterprise Agent Platform (GEAP). The role focuses on building scalable AI agents, enterprise integrations, & production-ready AI services. You will work closely with architects, platform engineers & business stakeholders to deliver secure, reliable, & cost-effective AI solutions.
Responsibilities
Design & develop AI agents, workflows, and integrations using Python.
Build integrations using APIGEE, REST APIs, & MCP
Develop solutions on GCP leveraging Gemini models, GEAP & Google AI services.
Implement prompt engineering, grounding, context management, RAG, & memory patterns.
Evaluate, test, deploy, monitor & optimize agent performance.
Analyze token consumption, model usage, scalability &operational costs.
Qualifications
5 + years Strong Python development experience for enterprise applications & AI solutions.
Hands-on experience with Agentic AI, multi-agent systems &orchestration patterns.
Solid understanding of GCP, Gemini models, GEAP, Vertex AI, or Google ADK.
Experience with APIGEE, APIs, integrations, &MCP-based connectivity.
Strong knowledge of model selection, prompt engineering, grounding, agent evaluation & cost monitoring
Key Responsibilities
Task Description: Job Description
Design, develop, deploy & support enterprise-grade Agentic AI solutions on Google Gemini Enterprise Agent Platform (GEAP). The role focuses on building scalable AI agents, enterprise integrations, & production-ready AI services. You will work closely with architects, platform engineers & business stakeholders to deliver secure, reliable, & cost-effective AI solutions.
Responsibilities
Design & develop AI agents, workflows, and integrations using Python.
Build integrations using APIGEE, REST APIs, & MCP
Develop solutions on GCP leveraging Gemini models, GEAP & Google AI services.
Implement prompt engineering, grounding, context management, RAG, & memory patterns.
Evaluate, test, deploy, monitor & optimize agent performance.
Analyze token consumption, model usage, scalability &operational costs.
Qualifications
5 + years Strong Python development experience for enterprise applications & AI solutions.
Hands-on experience with Agentic AI, multi-agent systems &orchestration patterns.
Solid understanding of GCP, Gemini models, GEAP, Vertex AI, or Google ADK.
Experience with APIGEE, APIs, integrations, &MCP-based connectivity.
Strong knowledge of model selection, prompt engineering, grounding, agent evaluation & cost monitoring